Our hands are much more likely to control the weather, especially when it comes to rain and mud. A possible storm, rain or hail may even cause us to postpone our work at times. But the annoying thing at this point is that we see light rain in the weather forecast and soon get soaked.
So why are weather apps sometimes wrong?
In fact, this problem is caused by meteorology rather than phone applications.
Examining weather events and making predictions accordingly, although related to science, requires long-term experience. There is no computer or single algorithm that can predict the weather 100% accurately.
Essentially, rather than a single algorithm, there are different forecast models and different interpretations of the data that allow various weather forecasts to be made for the same city. Data collected from various sources is processed using not one but multiple algorithms.
However, experts do not explain which data from which applications or which algorithms they use or how often they receive the data, and some erroneous readings occur. So, for example, an app like Dark Sky might show rain during the day, while AccuWeather only shows cloudy weather.
Phone apps compile weather data from a variety of sources.
The Weather Channel is the most advanced of these resources. The Weather Channel regularly shows the most accurate weather forecast, at about 82%, according to consultants who analyzed various forecast companies.
But that still means 18% of the data is wrong. This means that the weather forecast shown on 1.5 days out of 7 is not accurate and there is not much the phone companies can do about it.
Achieving near-perfect forecasts often requires the expertise of local meteorologists with years of experience in a particular region.
This accumulation of knowledge; It allows national weather companies to predict weather patterns with near-perfect accuracy. But the problem is that there is no way yet to compile these highly accurate local predictions.
Companies like The Weather Channel insist on making less accurate weather forecasts on their own and not relying on local companies.
For this reason, predictions such as storms or rain are sometimes not accurate.
In fact, the algorithms and the applications considered are improving day by day. The main reason for this is that over the years, more and more detailed data is included in the algorithms.
When it comes to temperature, forecasts are much closer to reality, but in case of precipitation or storms, it would be much more logical to trust local meteorologists.
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